Power companies utilize waste heat of gas turbines or the like to provide local heating water or provide high-pressure and low-pressure steam to plants. Petrochemical companies operate gas turbines and the like as power-supply facilities. In various plants and facilities utilizing gas turbines and the like, the discovery of anomaly of such devices at an early stage is extremely important in minimizing damages to the society.
In addition to gas turbines and steam turbines, there is a numerous list of facilities that must be subjected to detection of anomaly at an early stage, including water wheels in hydroelectric power plants, atomic reactors in atomic power plants, windmills in wind power plants, engines of aircrafts and heavy equipments, railway vehicles and rails, escalators, elevators, MRI and other medical equipment, manufacturing and inspecting devices for semiconductors and flat panel displays and so on, and further, device level or component level anomalies must be detected such as the deterioration or end of life of mounted batteries and the like. Recently, the importance of detecting anomaly (various symptoms) of the human body, such as the measurement and diagnosis/prognosis of brain waves for health management, is increasing.
As disclosed in patent literature 1 and patent literature 2, SmartSignal Corporation (US) provides a service of anomaly detection mainly targeting engines. Past data are stored in a database (DB), and the similarity between the observation data and past learning data are computed via a unique method to thereby compute an estimate value via linear coupling of data having high similarity so as to output the degree of deviation of the estimate value and the observation data. General Electric Company teaches detecting anomaly via k-means clustering as taught in patent literature 3.